Data Science Manager

Arch Insurance (UK) Limited
Southampton
4 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager – Property Tech – London

Data Science Manager – Property Tech – London

Manager, Data Science

Data Science and Analytics Manager

Data Science Product Intern (PhD Level) - Tesco

Data Science Product Intern (PhD Level)

Get AI-powered advice on this job and more exclusive features.

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.

Key Tasks & Responsibilities

  • Work closely with business partners to understand the business problems they are trying to solve and help develop and prioritize the best-suited analytics solutions.
  • Collaborate in cross-functional teams and share ideas to solve complex business problems.
  • Build strong partnerships with peers across the organization to support project goals and boarder team needs.
  • Oversee the build of predictive models using advanced analytics techniques including GLMs, natural language processing, and machine learning.
  • Develop powerful insights using a variety of analytical tools, techniques, and technologies, and deliver results which drive business decisions.
  • Discover, explore, and analyse internal and external datasets for the purpose of developing advanced analytics models.
  • Help establish best practices and repeatable processes for the Strategic Analytics team.
  • Provide thought leadership on new, innovative techniques, approaches and software.
  • Guide, support, mentor and develop the growing team of predictive modelers and data scientists.

Desired Skills

  • Ability to design, build and implement statistical models, with an understanding of a range of analytical techniques such as predictive modelling, NLP and data mining.
  • Data manipulation and analytical skills in languages such as Python, R and / or SQL.
  • Familiarity with cloud-based platforms such as Databricks, Snowflake and Azure is an advantage, but not essential.
  • Effective task / project management and general organization skills.
  • Excellent verbal and written communications skills; ability to convey complex concepts to technical and non-technical people across the organization.
  • Exceptional teamwork skills required to play a key role in cross-functional teams. Ability to collaborate and build trusting relationships with business partners.
  • Natural curiosity to understand the world around you and question as needed.
  • Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces.
  • Ability to apply critical thinking and creative problem-solving skills.

Experience

  • Experience in advanced analytics roles, a significant portion of which should be in the insurance industry.
  • Experience working in an analytical role within an insurance environment is an advantage.
  • Hands-on experience developing and deploying real-time predictive models.
  • Experience delivering business value from small or non-standard data sets.

Qualifications

  • Degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you. If this job isn’t the right fit but you’re interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch’s Talent Acquisition team.

14101 Arch Europe Insurance Services LtdSeniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionEngineering and Information Technology
  • IndustriesInsurance

Referrals increase your chances of interviewing at Arch Insurance (UK) Limited by 2x

Chandler's Ford, England, United Kingdom 1 day ago

Chandler's Ford, England, United Kingdom 2 weeks ago

Southampton, England, United Kingdom 1 day ago

Southampton, England, United Kingdom 2 days ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.